Single-cell measurements unveil surprising universality

Different genes in the cell are regulated by a wealth of different molecular mechanisms. Yet, when the temporal expression pattern of many genes is examined in individual cells, a surprising degree of universality is observed.

Gene activity is the prime mover in the living cell, driving a cell’s function at any given time. Gene expression is regulated largely at the level of transcription, i.e. by varying the production of RNA from the gene. Different “transcriptional programs”, where a set of genes exhibits a specific expression pattern, define distinct cellular behaviors (phenotypes). Such phenotypes range from the way a simple bacterium adapts to changes in nutrient level, to the way a cell in the developing human embryo establishes its differentiated state.

In the Golding lab, we have been using high-resolution fluorescence microscopy to examine transcription kinetics in individual cells. Transcription events are followed in individual living cells, and “snapshots” of RNA copy-number statistics are obtained from a large population of cells. In previous studies of E. coli, we found that the kinetics of RNA production cannot be described as a simple Poisson process. That is, RNA is not produced with a constant probability in time. Instead, we found that RNA production occurs in a “bursty”, intermittent manner.

This temporal intricacy of gene activity led us to ask: How is the time-series of transcription events modulated when gene expression level varies? For example, increasing RNA production could be achieved by increasing either the rate of transcription bursts, the duration of individual bursts, or the rapidity in which RNA is produced during a bursting event. Different genes in different organisms may be expected to display diverse “modulation schemes”, based on the molecular details of transcriptional regulation. However, our recent work suggests that this is not the case. Instead, when examining 20 different genes in E. coli, under >50 different expression conditions, we found a surprising degree of universality: The properties of the transcriptional time-series were independent of the identity and molecular details of the gene, and depended only on the expression level. Furthermore, the observed behavior was explained by a simple underlying scenario, in which expression level is varied by only changing the duration of transcription bursts while leaving other kinetic parameters constant. Thus, a simple scaling law, relating the degree of burstiness with expression level, could be formulated, which holds for multiple genes and expression levels.

This work was done in collaboration with the group of Ronen Segev (Israel), my HFSP co-PI. Together with our third co-PI, Satoshi Sawai (Japan), we aim to better understand the way living cells process information from their environment and make decisions based on that information.